The DAEDALOS project has delivered a comprehensive set of results bridging power system planning and real-time grid operation. Central to these achievements is a modular software platform built on an Apache Kafka process bus, enabling vendor-independent data exchange between modern SCADA systems and external analytical tools. Key outputs include steady-state and short-circuit analysis tools accounting for the non-linear behavior of power converters, an optimization-based grid planning tool for hybrid AC/DC networks, and advanced algorithms for inertia estimation. In addition, a validated decision support tool was developed to detect low-frequency oscillations using real-time PMU data, alongside innovative ancillary services aimed at preventing system splits and enhancing grid resiliency. These solutions will be validated through two realistic demonstrators at RWTH and UPC, providing near-real control room environments and achieving TRL 6–7.
The impacts of DAEDALOS span scientific, societal, and economic dimensions. Scientifically, advances in oscillation analysis are expected to influence future TSO/DSO requirements, power electronic device design, and related publications and patents. Societally, the project supports the European Green Deal by improving grid reliability and security under high renewable penetration, contributing to CO2 emission reductions. Economically, DAEDALOS solutions could deliver significant savings, including around €100 million annually through redispatch optimization if widely adopted, and €50 million over ten years by avoiding moderate outages. The project also targets entry into the growing digital utility market, forecast to reach nearly $400 billion globally by 2030.
To ensure long-term uptake, several needs must be addressed particularly by identifying gaps in European grid codes and providing policy recommendations for DC technology deployment. Further validation is required to reduce risk and demonstrate interoperability across vendors. Market uptake will rely on tailored business models, structured training, and effective knowledge transfer, while overcoming political, legal, and social barriers will require sustained stakeholder engagement and collaboration with environmental organizations.